Use of Geospatial data for disaster managements

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Use of Geospatial data for disaster managements Source: http://alertsystemsgroup.com Instructor : Professor Dr. Yuji Murayama Teaching Assistant : Manjula Ranagalage

What is GIS? A powerful set of tools for collecting, storing, retrieving, transforming and displaying spatial data for the real world (Burrough,1986) An organized collection of computer hardware, software, geographic data and personnel designed to efficiently capture store, update, manipulate, analyze and display all forms geographically referenced information ( Understanding GIS - ESRI )

What is Disaster Disaster can be defined as a serious disruption of the functioning of a community or a society causing widespread human, material, economic or environmental losses which exceed the ability of the affected community or society to cope using its own resources (UNISDR, 2009) 3

What is Risk Assessment? Risk assessment is a systematic process for collecting and analyzing information for determining and addressing needs, or gaps between current conditions or existing problems for determining priorities, preparing plans and allocating funds and resources to bring about the desired changes or behaviors, based on the strengths and capacities of the community. Risk assessment includes hazard, vulnerability and capacity assessments during pre and post disaster situations in a particular community (UNISDR, 2009) Geospatial data plays an important role in disaster risk assessment and management 4

Use of Geospatial Data for Disaster Management Satellite image classification helps to identify the extent of damages due to disasters (pre-disaster and post-disaster) Time-series images analysis provides to identify the level of risk and damages Tracking hurricanes and storm Locating temporally shelter for victims Identifying population changes in disaster areas Monitoring construction after disasters Identifying the protected roads for evacuation Helping to develop effective disaster management plans Contributing to hazard and vulnerability assessments 5

landslide Damage assessments Landslide hazards mapping Rainfall mapping Land use and land cover changes Landslide vulnerability mapping Find location for resettlement Evacuation path Drought Drought impact assessments Land use cover change analysis Risk and vulnerability assessment Early waning Weather forecasting Mapping crop damages Cyclone Risk modeling Early warning Identify escape routs Damage assessments Cyclone monitoring Geo-spatial Data Sea level rise Damage assessments Sea level rise mapping Coastal belt changes mapping Sea level rise vulnerability mapping Identification of the spatial and temporal changes of sea level rise Tsunami Early warnings Tsunami damage assessments Tsunami vulnerability assessments Tsunami risk mapping Tsunami inundation mapping Vertical and horizontal Evacuation plans Effected population mapping Flood Early warnings Flood damage assessments Flood vulnerability assessments Rainfall mapping Flood routing model Evacuation models Rainfall monitoring 6

Use of Geospatial Data GIS and remote sensing data helps to prepare effective disaster management plans Spatial data can be used to develop a disaster framework for disaster managers and planners in different stages in disaster management cycle It contributes to minimize the damage of disasters to the community Disaster management cycle Source: www.quora.com/what-is-disaster-management-cycle

Use of Geospatial Data for Disaster Management Stages Stages Contribution of geospatial data for disaster management Preparation Identifying emergency areas Positioning relevant resources (physical and Human) Developing short term and long term strategies Developing early warning systems Conducting disaster education for community Developing evacuation plans, hospital disaster plans (participatory approaches) Conducting disaster drills to identify the response of community and relevant agencies Response Providing accurate information on disaster emergency location Using already developing evacuation plains to action Managing resource effectively Distributing basic needs without delay (food, medicine, temporally salters) Recovery Restoring, rebuilding and reshaping the disaster areas Preparing short and long terms recovery plans Preparing damage maps Keeping records of information about the deaths, injured people, impact to ecosystems and damage infrastructure (houses, roads, schools, hospitals, etc.) Providing life support systems (temporally housing, health care, counseling programs) Conducting socio-economic impact studies Updating hazard, vulnerability and risk databases Mitigation Preventing future threat of disaster Minimizing the damage of future disasters Conducting hazard and vulnerability assessments Developing or shaping mitigation plans and policies 8

Case Study 1 Title: Flood hazard mapping and damage assessment in lower basin of Kelani river 9

Introduction Flood Hazard Mapping is a vital component for appropriate planning in flood-prone areas. It creates easily-read, rapidlyaccessible charts and maps. It will help administrators and planners to identify areas of risk According to the World Methodological Organization (WMO), hazard area mapping is a important event in the disaster mitigation process Damage assessment is also vitally important in the disaster management process 10

Objectives Preparation of flood hazard maps for different elevation ranges in the lower basin of Kelani river Demarcating the inundation area and calculating damage assessment in different elevation ranges 11

Importance of Study Floods in Kelani river are important due to its outfall being near the capital City of Colombo. It covers two densely populated districts of the country. Colombo and Gampaha districts which are frequently and considerably affected by flood events According to the history, floods in 1930 reached a level of 10.9 feet msl. In 1940 floods reached a level of 11.06 feet MSL. In 1947, flood level reached 12.05 feet MSL Identification of different levels of inundation areas is essential in the flood management process. This study was carried out for hazard mapping and damage assessment of the lower basin of Kelani River 12

Study Area Length 145 km Forth longest river in the country Catchment area 2230 km 2 water discharge to sea Dry seasons - 20 m 3 /s to 25 m 3 /s Monsoon season - 800 m 3 /s to 1,500 m 3 /s The average annual rainfall in the basin - 2400 mm Sri Lanka Kalani Rever Basin Kilometers 0 2.5 5 10 15 20 13

Flood Limit in Kelani basin at Colombo Minor flood = 5 7 feet (1.5-2.1 meter) Major flood = 7 9 feet (2.1-2.7 meter) Dangerous flood = 9 12 feet (2.7 3.7 meter) Critical flood = above 12 feet (above 3.7 meter) Source: Irrigation Department, 2004 14

Required Data Maps Scale Source River network 1:10000 Survey department Land use 1:10000 Survey department Buildings 1:10000 Survey department Roads 1:10000 Survey department Contour 1:10000 Survey department GN divisions High resolution satellite images One meter Census and statistics department 15

Methodology Contour TIN model DEM flood hazard map area in meter 1, 2, 3 & 4 Human settlements Other buildings Infrastructures Land use GN divisions River network Calculate Building Land use Roads High resolution satellite images Cell base analysis Intersect Demarcate & calculate area of inundation In deferent flood ranges Inundation area >=50% of Total area Most vulnerable Inundation area 50 % -25% of Total area vulnerable Inundation area <=25% of Total area less vulnerable Overlay Vulnerable areas 1 meter flood level damage 2 meter flood level damage 3 meter flood level damage 4 meter flood level damage 16

Cont Flood level 1 meter flood level 2 meter flood level 3 meter flood level 4 meter flood level Flood distribution maps Damage assessment Vulnerable GN divisions Maps & tables Human dettlements Other buildings Infrastructures Land use Most vulnerable vulnerable Less vulnerable 17

Output - Tables Damage of roads Flood level 1 meter Length of main road Length of miner road Length of jeep & cart track Length of railway 2 meter 3 meter 4 meter Flood level 1 meter 2 meter 3 meter 4 meter No of buildings Damage of buildings Damage of land use Flood level Home garden Forest Build up area Paddy Other plantations 1 meter 2 meter 3 meter 4 meter

Case Study 2 Title: Flood routing model: A case study of Rathnapura town area, Sri Lanka 19

Introduction Floods along the Kalu river from the most upstream major town. Ratnapura City makes great inconvenience to the people economically and socially Source: www.sundayobserver.lk Source: www.redcross.lk 20

Objectives Developing the flood routing model around Ratnapura City area based on Kalu river Predicting flood levels along the river to minimize the damages 21

Study Area 22

Required Data Data Source Year Contour map (1:10000), (1:5000) Survey department 2010 Spot height Survey department 2010 Land use data Survey department 2010 Soil type data Agriculture department 2010 Rainfall data Meteorological department 1989-2009 Runoff data Irrigation department 1989-2009 Cross section data Irrigation department 2007 23

Methodology DEM of the study area Topographic map(1:10000) Land use Cross section of the river Run-off water Rainfall Hec Geo Ras HEC -Ras River center line, banks Flow path cross section cut line Flow profile Hec - GeoRas Flood routing model 23

Results Rainfall data is 250 350mm, Result of Runoff is 105-150 mcm. Flood was gone to 13m Mean Sea Level (MSL) contour level 0 Flood level river is started to flood. Rainfall data is 350 400mm, result of runoff is 150-170 mcm. Flood was gone to 19m MSL contour level Blue area is risk area 25

Rainfall data is 400 500mm and result of runoff is 170-220mcm. Flood is gone to 21m MSL contour level Blue area is risk area Intermediate flood level Rainfall data is more than 500mm and result of runoff is more than 220 mcm. Flood is gone to 24m MSL contour level High flood level 25

Recommendation for Future Developments It is recommended to use additional rainfall stations around the catchment area so that the aerial distribution of rainfall can be represented well This study uses only 20 years of hourly rainfall and water level data. It is recommended to use a longer time series data for calibration and validation of this model 27

References Burrough, P.A., 1986. Principles of Geographical Information Systems for Land Resources Assessment. Oxford: Clarendon. Environmental Systems Research Institute., 1995. Understanding GIS: the ARC/INFO method: self-study workbook : PC version. Geoformation International, California, USA United Nations., 2009. UNISAR terminology on Disaster Risk Reduction. Geneva, Switzerland http://alertsystemsgroup.com www.quora.com www.sundayobserver.lk www.redcross.lk 28